---
tags:
- spacy
- token-classification
language:
- fr
model-index:
- name: fr_arches_ner
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.6778376222
    - name: NER Recall
      type: recall
      value: 0.7156697557
    - name: NER F Score
      type: f_score
      value: 0.6962401393
---
| Feature | Description |
| --- | --- |
| **Name** | `fr_arches_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.6.1,<3.7.0` |
| **Default Pipeline** | `tok2vec`, `ner`, `entity_punctuation_removal` |
| **Components** | `tok2vec`, `ner`, `entity_punctuation_removal` |
| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |

### Label Scheme

<details>

<summary>View label scheme (15 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`ner`** | `CHRONOLOGIE`, `DECOR`, `EDIFICE`, `ESPECE`, `GPE`, `ID`, `LIEUDIT_SITE`, `LOC`, `MATERIAU`, `MOBILIER`, `ORG`, `PERSONNE`, `PEUPLE_CULTURE`, `STRUCTURE`, `TECHNIQUE_STYLE` |

</details>

### Accuracy

| Type | Score |
| --- | --- |
| `ENTS_F` | 69.62 |
| `ENTS_P` | 67.78 |
| `ENTS_R` | 71.57 |
| `TOK2VEC_LOSS` | 63436.09 |
| `NER_LOSS` | 246059.83 |